## SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.# SPDX-License-Identifier: Apache-2.0## Licensed under the Apache License, Version 2.0 (the "License");# you may not use this file except in compliance with the License.# You may obtain a copy of the License at## http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing, software# distributed under the License is distributed on an "AS IS" BASIS,# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.# See the License for the specific language governing permissions and# limitations under the License.#fromtripyimportexport,constraints
[docs]@export.public_api(document_under="operations/functions")@constraints.dtypes(constraints={"input":"T1",constraints.RETURN_VALUE:"T1"},variables={"T1":["float32","float16","bfloat16","int4","int32","int64","bool","int8"],},)defrelu(input:"tripy.Tensor")->"tripy.Tensor":r""" Applies Rectified Linear Unit (RELU) function to each element of the input tensor: :math:`\text{relu}(x) = \max(0,x)` Args: input: The input tensor. Returns: A tensor of the same shape as the input. .. code-block:: python :linenos: :caption: Example input = tp.Tensor([1., 2., 3., 4.], dtype=tp.float32) output = tp.relu(input) t = torch.tensor([1, 2, 3, 4], dtype=torch.float32) # doc: omit assert tp.allclose(output, tp.Tensor(torch.nn.functional.relu(t))) """fromtripy.frontend.opsimportzerosfromtripy.frontend.trace.ops.binary_elementwiseimportmaximummask=zeros((1,),dtype=input.dtype)returnmaximum(mask,input)